Systems and methods for managing a multi-listing combined offer are provided. A networked system receives an indication to add a combination of items from multiple sellers into a virtual cart. In response, the networked system causes presentation of a user interface showing a combination of items from multiple sellers. The networked system receives, from the buyer, a buyer offer price for the combination of items. In response, the networked system accesses, from a data storage, item information for each item of the combination of items, whereby the item information includes a seller identifier, an original item price, and shipping cost for each item. The networked system then generates, based on the accessed item information and the buyer offer price, a split offer price for each seller, whereby the split offer price is a split of the buyer offer price. The split offer price is then presented to each corresponding seller.
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5. The method of claim 4, wherein the shipping cost for a seller of the multiple sellers is less than a summation of individual shipping cost for each of the items from the seller, the shipping cost being based on combining shipping of at least two of the items in the virtual cart into a single shipping container.
This invention relates to optimizing shipping costs for sellers in an e-commerce environment. The problem addressed is the inefficiency of individual shipping for multiple items from the same seller, which leads to higher costs for both sellers and buyers. The solution involves a method for reducing shipping expenses by consolidating items from the same seller into a single shipping container, rather than shipping each item separately. The method calculates the shipping cost for the seller based on the combined shipment, which is lower than the sum of individual shipping costs for each item. This approach leverages economies of scale in shipping, reducing overall logistics expenses while maintaining efficient delivery. The system identifies items in a virtual cart that are eligible for consolidation, ensuring compatibility with shipping constraints such as size, weight, and delivery destination. By bundling items from the same seller, the method minimizes packaging and transportation costs, benefiting both sellers and buyers through lower fees and potentially faster delivery times. The solution is particularly useful in multi-seller marketplaces where multiple vendors may contribute items to a single order.
8. The method of claim 1, wherein the identifying the one or more recommended items comprises identifying at least one recommended item from a wishlist or watchlist of the buyer that is related to an item in the virtual cart.
This invention relates to e-commerce systems that recommend items to buyers based on their wishlists or watchlists. The problem addressed is the inefficiency of traditional recommendation systems that fail to leverage a buyer's pre-existing interest in items they have saved but not yet purchased. The invention improves upon prior art by dynamically identifying and suggesting items from a buyer's wishlist or watchlist that are related to items already in their virtual shopping cart. This enhances the shopping experience by providing personalized, contextually relevant recommendations that align with the buyer's known preferences. The system analyzes the relationship between items in the cart and those in the wishlist or watchlist, such as through shared categories, attributes, or complementary use cases, to generate tailored suggestions. This approach increases the likelihood of additional purchases while reducing the cognitive load on the buyer by surfacing items they have already expressed interest in. The method operates in real-time, ensuring recommendations remain relevant as the cart contents change. This solution is particularly useful in online retail environments where maximizing conversion rates and user engagement is critical.
9. The method of claim 1, wherein the identifying the one or more recommended items comprises identifying at least one recommended item that is related to an item in the virtual cart and an item previous purchased by the buyer.
This invention relates to a method for recommending items to a buyer in an e-commerce system. The problem addressed is the need to provide personalized and relevant product recommendations to buyers based on their current and past purchasing behavior. The method identifies one or more recommended items by analyzing the contents of a virtual cart and the buyer's purchase history. Specifically, the method determines at least one recommended item that is related to both an item currently in the virtual cart and an item previously purchased by the buyer. This ensures that the recommendations are contextually relevant, leveraging both immediate and historical shopping data to enhance the buyer's experience. The method may involve analyzing relationships between items, such as complementary products, frequently co-purchased items, or items with similar attributes. By cross-referencing the virtual cart contents with past purchases, the system generates more accurate and personalized recommendations, potentially increasing sales and customer satisfaction. The approach improves upon traditional recommendation systems that rely solely on either cart contents or purchase history, providing a more holistic and dynamic solution.
14. The system of claim 13, wherein the shipping cost for a seller of the multiple sellers is less than a summation of individual shipping cost for each of the items from the seller, the shipping cost being based on combining shipping of at least two of the items in the virtual cart into a single shipping container.
This invention relates to a system for optimizing shipping costs in an e-commerce environment where multiple sellers offer items for sale. The problem addressed is the inefficiency of individual shipping costs when multiple items from the same seller are purchased separately, leading to higher overall shipping expenses for both the seller and the buyer. The system improves upon this by combining at least two items from the same seller in a virtual cart into a single shipping container, thereby reducing the total shipping cost for the seller compared to the sum of individual shipping costs for each item. The system dynamically evaluates shipping options to determine the most cost-effective method for consolidating items from the same seller, ensuring that the combined shipping cost is lower than the sum of individual shipping costs. This approach minimizes shipping expenses while maintaining efficient logistics for both sellers and buyers. The system may also integrate with inventory management and order fulfillment processes to streamline the consolidation of items into a single shipment. By reducing shipping costs, the system enhances profitability for sellers and provides cost savings for buyers, making the overall purchasing process more efficient.
17. The system of claim 10, wherein the identifying the one or more recommended items comprises identifying at least one recommended item from a wishlist or watchlist of the buyer that is related to an item in the virtual cart.
This invention relates to e-commerce systems that recommend items to buyers based on their wishlists or watchlists. The problem addressed is the inefficiency of buyers manually searching for related items while shopping, leading to missed opportunities for cross-selling and a suboptimal user experience. The system identifies one or more recommended items for a buyer by analyzing their wishlist or watchlist and determining if any items in these lists are related to an item already in the buyer's virtual cart. The relationship between items can be based on factors such as product category, brand, or user behavior data. The system then presents these recommended items to the buyer, encouraging additional purchases and improving the shopping experience. The system may also track buyer interactions with the recommendations, such as clicks or purchases, to refine future suggestions. Additionally, the system can prioritize recommendations based on relevance, recency, or other criteria to enhance personalization. The overall goal is to streamline the shopping process by automatically surfacing relevant items from the buyer's wishlist or watchlist, increasing engagement and conversion rates.
18. The system of claim 10, wherein the identifying the one or more recommended items comprises identifying at least one recommended item that is related to an item in the virtual cart and an item previous purchased by the buyer.
This invention relates to a recommendation system for e-commerce platforms that identifies and suggests items to a buyer based on their current virtual cart and past purchase history. The system addresses the challenge of providing personalized and relevant product recommendations to enhance the shopping experience and increase sales conversion rates. The system operates by analyzing the contents of a buyer's virtual cart, which includes items the buyer has selected but not yet purchased. It then cross-references these items with the buyer's previous purchases to identify patterns or relationships between the current selections and past buying behavior. Based on this analysis, the system generates a list of recommended items that are likely to be of interest to the buyer. The recommendations are tailored to complement the items already in the cart or to suggest items that the buyer may have previously purchased or shown interest in. The system may also consider additional factors such as item popularity, buyer demographics, or seasonal trends to refine the recommendations. The goal is to provide a seamless and intuitive shopping experience by anticipating the buyer's needs and offering relevant suggestions in real-time. This approach helps buyers discover new products while increasing the likelihood of completing a purchase.
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May 9, 2023
April 23, 2024
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